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Siddhartha Chib is an econometrician, statistician, and the Harry C. Hartkopf Professor of
Econometrics Econometrics is an application of statistical methods to economic data in order to give empirical content to economic relationships. M. Hashem Pesaran (1987). "Econometrics", '' The New Palgrave: A Dictionary of Economics'', v. 2, p. 8 p. 8 ...
and
Statistics Statistics (from German language, German: ', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a s ...
at Washington University in St. Louis. His work is primarily in
Bayesian statistics Bayesian statistics ( or ) is a theory in the field of statistics based on the Bayesian interpretation of probability, where probability expresses a ''degree of belief'' in an event. The degree of belief may be based on prior knowledge about ...
, econometrics, and Markov chain Monte Carlo methods. Chib's research spans a wide range of topics in Bayesian statistics, with influential contributions to statistical modeling, computational methods, and Bayesian model comparison techniques.


Career

Albert and Chib (1993) pioneered a latent variable framework that greatly simplified estimation of binary and categorical response models and became a foundational method in Bayesian statistics. This framework was later extended to the multivariate setting in Chib and Greenberg (1998), which provided a flexible and coherent approach for modeling correlated discrete outcomes. Chib and Greenberg (1995), a widely cited and influential paper, provides a unified and intuitive framework for understanding the Metropolis–Hastings algorithm and its extensions in high-dimensional settings. Drawing on the fundamental principles of global and local reversibility, the authors provide derivations of both the single-block and multiple-block forms of the algorithm, and guidance on implementation. Chib (1995) introduced a scalable and widely adopted solution to calculating the marginal likelihood for Bayesian model comparisons. The method relies on an identity that expresses the marginal likelihood as the product of the likelihood and the prior, divided by the posterior ordinate at a fixed point in the parameter space. Chib showed that this posterior ordinate can be factorized into a sequence of marginal and conditional posterior densities, each estimable from MCMC output. The approach was later extended by Chib and Jeliazkov (2001) to Metropolis-Hastings chains and by Basu and Chib (2003) to nonparametric Bayesian models based on Dirichlet process mixtures. Carlin and Chib (1995) contains an influential Markov chain Monte Carlo method for model selection that involves jumps between model spaces. The approach has proved useful for comparing complex Bayesian models. Kim, Shephard, and Chib (1998) developed a key method for estimating stochastic volatility models. Extensions to student-t models, covariates, high dimensional time series and models with leverage appear in Chib, Nardari and Shephard (2002), Chib, Nardari and Shephard (2006) and Omori et al. (2007). Chib (1998) presents a reparameterization of a change point model as a unidirectional hidden Markov model (HMM) that simplifies estimation and inference and enables the use of efficient forward-filtering and backward-sampling techniques for HMMs developed in Chib (1996) and Albert and Chib (1993). Chib has also worked on and developed original methods for Bayesian inference in Tobit censored responses, discretely observed diffusions, univariate and multivariate ARMA processes, multivariate count responses, causal inference, hierarchical models of longitudinal data, nonparametric regression, and tailored randomized block MCMC methods for complex structural models. Chib, Shin, and Simoni (2018, 2022) consider Bayesian inference in models that do not specify a parametric or non-parametric data generating process.


Biography

Chib received a bachelor's degree from St. Stephen’s College, Delhi, in 1979, an M.B.A. from the Indian Institute of Management, Ahmedabad, in 1982, and a Ph.D. in economics from the
University of California, Santa Barbara The University of California, Santa Barbara (UC Santa Barbara or UCSB) is a Public university, public Land-grant university, land-grant research university in Santa Barbara County, California, United States. Tracing its roots back to 1891 as an ...
, in 1986. His advisors were Sreenivasa Rao Jammalamadaka and Thomas F. Cooley.


Honors and awards

Chib is a fellow of the American Statistical Association (2001), an inaugural fellow of the International Society of Bayesian Analysis (2012), and a fellow of the Journal of Econometrics (1996).


Selected publications

* Albert, Jim; Chib, Siddhartha (1993)
Bayesian Analysis of "Binary and Polychotomous Response Data"
'' Journal of the American Statistical Association,'' 88(2), 669–679. *Chib, Siddhartha; Greenberg, Edward (1995)
"Understanding the Metropolis–Hastings Algorithm"
'' American Statistician'', 49(4), 327–335. *Chib, Siddhartha (1995)
"Marginal Likelihood from the Gibbs Output"
'' Journal of the American Statistical Association'', 90(4), 1313–1321. *Carlin, Brad; Chib, Siddhartha (1995)
"Bayesian Model Choice via Markov Chain Monte Carlo Methods"
'' Journal of the Royal Statistical Society, Series B'', 57(3), 473–484. *Chib, Siddhartha (1996)
"Calculating Posterior Distributions and Modal Estimates in Markov Mixture Models"
'' Journal of Econometrics'', 75, 79–97. * * Kim, Sangjoon; Shephard, Neil; Chib, Siddhartha (1998). "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models", '' Review of Economic Studies'', 65, 361–393. *Chib, Siddhartha (1998).
Estimation and Comparison of Multiple Change Point Models
. '' Journal of Econometrics'', 86, 221-241. *Chib, Siddhartha; Greenberg, Edward (1998)
"Analysis of Multivariate Probit Models"
'' Biometrika'', 85, 347-361. *Chib, Siddhartha; Jeliazkov, Ivan (2001)
"Marginal Likelihood from the Metropolis-Hastings Output"
'' Journal of the American Statistical Association'', 96(1), 270-281. * * *Chib, Siddhartha; Nardari, Federico; Shephard, Neil (2002)
"Markov Chain Monte Carlo Methods for Stochastic Volatility Models"
'' Journal of Econometrics'', 108, 281-316. * * * *Chib, Siddhartha; Ramamurthy, Srikanth (2010)
"Tailored randomized block MCMC methods with application to DSGE models"
'' Journal of Econometrics'', 155, 19-38. *Chib, Siddhartha; Shin, Minchul; Simoni, Anna (2018)
"Bayesian Estimation and Comparison of Moment Condition Models"
'' Journal of the American Statistical Association'', 113(4), 1656-1668. *Chib, Siddhartha; Shin, Minchul; Simoni, Anna (2022). "Bayesian Estimation and Comparison of Conditional Moment Models".
Journal of the Royal Statistical Society, Series B
84 (3), 740–764.


References


External links


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* {{DEFAULTSORT:Chib, Siddhartha Living people Bayesian statisticians University of California, Santa Barbara alumni Washington University in St. Louis faculty Delhi University alumni Econometricians Fellows of the American Statistical Association Year of birth missing (living people) Indian Institute of Management Ahmedabad alumni St. Stephen's College, Delhi alumni 20th-century Indian economists 21st-century Indian economists Indian emigrants to the United States Indian statisticians